These replication files allow one to replicate the figures reported in the article “Politics Ex Cathedra: Religious Authority and the Pope in Modern International Relations" as well as its supplemental Appendix.

This folder contains the following files:

	⁃ The R script “encyclicals.R”, which replicates all the data arrangements and all the analyses presented in the main paper. The script generates the perplexity and log-likelihood metrics for topic number identification (Figure 1), the cohesiveness vs exclusivity plot (Figure 2), the 2-topic LDA model (Figure 3), the Structural Topic Model coefficient plot (Figure 5), and the Laudato Si 2-topic LDA model (Figure 6), as well as the supplementary word frequency plots (Figure A.1), the additional validity plot (Figure A.2), the Wordfish robustness test (Figure A.3) and the Laudato Si word frequency plot (Figure A.4);

	⁃ The folder “figures”, which includes all the plots generated through “encyclicals.R”;

	⁃ The folder “encyclicals_it” that includes all of the text files (encyclicals in txt format):
		⁃ The subfolder “encyclicals_it_re”  is used for the main model fit and the primary analyses. Specifically, these txt files are used to generate Figure 1, Figure 3, Figure A.3, and to generate the text included in the data frame “encycl_stm.csv” that is used for Figure 2 and Figure 5;
		⁃ The subfolders “encyclicals_it_leastpolitical” and “encyclicals_it_mostpolitical” are used to separate the encyclicals distinguished via Figure 3, and also to generate the frequency bars at Figure A.1;

	⁃ The folder “encyclicals_model fit output”, which includes the full set of model fit output generated through “encyclicals.R” under Topic number identification;

	⁃ The folder “laudato_si”, which includes the full text of the 2015 encyclical and is used to generate Figure 6 and Figure A.4;

	⁃ The file “encycl_semanticvalid.csv”, which includes the qualitative data that validates the LDA topic model analyses and is used to generate Figure A.2;

	⁃ The file “encycl_stm.csv”, which is used to perform the Structural Topic Model analysis and to generate Figures 2 and 5.

